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<FONT color="green">001</FONT>    /*<a name="line.1"></a>
<FONT color="green">002</FONT>     * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a>
<FONT color="green">003</FONT>     * contributor license agreements.  See the NOTICE file distributed with<a name="line.3"></a>
<FONT color="green">004</FONT>     * this work for additional information regarding copyright ownership.<a name="line.4"></a>
<FONT color="green">005</FONT>     * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a>
<FONT color="green">006</FONT>     * (the "License"); you may not use this file except in compliance with<a name="line.6"></a>
<FONT color="green">007</FONT>     * the License.  You may obtain a copy of the License at<a name="line.7"></a>
<FONT color="green">008</FONT>     *<a name="line.8"></a>
<FONT color="green">009</FONT>     *      http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a>
<FONT color="green">010</FONT>     *<a name="line.10"></a>
<FONT color="green">011</FONT>     * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a>
<FONT color="green">012</FONT>     * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a>
<FONT color="green">013</FONT>     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a>
<FONT color="green">014</FONT>     * See the License for the specific language governing permissions and<a name="line.14"></a>
<FONT color="green">015</FONT>     * limitations under the License.<a name="line.15"></a>
<FONT color="green">016</FONT>     */<a name="line.16"></a>
<FONT color="green">017</FONT>    <a name="line.17"></a>
<FONT color="green">018</FONT>    package org.apache.commons.math3.random;<a name="line.18"></a>
<FONT color="green">019</FONT>    <a name="line.19"></a>
<FONT color="green">020</FONT>    import java.io.BufferedReader;<a name="line.20"></a>
<FONT color="green">021</FONT>    import java.io.File;<a name="line.21"></a>
<FONT color="green">022</FONT>    import java.io.FileInputStream;<a name="line.22"></a>
<FONT color="green">023</FONT>    import java.io.IOException;<a name="line.23"></a>
<FONT color="green">024</FONT>    import java.io.InputStream;<a name="line.24"></a>
<FONT color="green">025</FONT>    import java.io.InputStreamReader;<a name="line.25"></a>
<FONT color="green">026</FONT>    import java.net.URL;<a name="line.26"></a>
<FONT color="green">027</FONT>    import java.nio.charset.Charset;<a name="line.27"></a>
<FONT color="green">028</FONT>    import java.util.ArrayList;<a name="line.28"></a>
<FONT color="green">029</FONT>    import java.util.List;<a name="line.29"></a>
<FONT color="green">030</FONT>    <a name="line.30"></a>
<FONT color="green">031</FONT>    import org.apache.commons.math3.distribution.AbstractRealDistribution;<a name="line.31"></a>
<FONT color="green">032</FONT>    import org.apache.commons.math3.distribution.NormalDistribution;<a name="line.32"></a>
<FONT color="green">033</FONT>    import org.apache.commons.math3.distribution.RealDistribution;<a name="line.33"></a>
<FONT color="green">034</FONT>    import org.apache.commons.math3.exception.MathIllegalStateException;<a name="line.34"></a>
<FONT color="green">035</FONT>    import org.apache.commons.math3.exception.MathInternalError;<a name="line.35"></a>
<FONT color="green">036</FONT>    import org.apache.commons.math3.exception.NullArgumentException;<a name="line.36"></a>
<FONT color="green">037</FONT>    import org.apache.commons.math3.exception.OutOfRangeException;<a name="line.37"></a>
<FONT color="green">038</FONT>    import org.apache.commons.math3.exception.ZeroException;<a name="line.38"></a>
<FONT color="green">039</FONT>    import org.apache.commons.math3.exception.util.LocalizedFormats;<a name="line.39"></a>
<FONT color="green">040</FONT>    import org.apache.commons.math3.stat.descriptive.StatisticalSummary;<a name="line.40"></a>
<FONT color="green">041</FONT>    import org.apache.commons.math3.stat.descriptive.SummaryStatistics;<a name="line.41"></a>
<FONT color="green">042</FONT>    import org.apache.commons.math3.util.FastMath;<a name="line.42"></a>
<FONT color="green">043</FONT>    import org.apache.commons.math3.util.MathUtils;<a name="line.43"></a>
<FONT color="green">044</FONT>    <a name="line.44"></a>
<FONT color="green">045</FONT>    /**<a name="line.45"></a>
<FONT color="green">046</FONT>     * &lt;p&gt;Represents an &lt;a href="http://http://en.wikipedia.org/wiki/Empirical_distribution_function"&gt;<a name="line.46"></a>
<FONT color="green">047</FONT>     * empirical probability distribution&lt;/a&gt; -- a probability distribution derived<a name="line.47"></a>
<FONT color="green">048</FONT>     * from observed data without making any assumptions about the functional form<a name="line.48"></a>
<FONT color="green">049</FONT>     * of the population distribution that the data come from.&lt;/p&gt;<a name="line.49"></a>
<FONT color="green">050</FONT>     *<a name="line.50"></a>
<FONT color="green">051</FONT>     * &lt;p&gt;An &lt;code&gt;EmpiricalDistribution&lt;/code&gt; maintains data structures, called<a name="line.51"></a>
<FONT color="green">052</FONT>     * &lt;i&gt;distribution digests&lt;/i&gt;, that describe empirical distributions and<a name="line.52"></a>
<FONT color="green">053</FONT>     * support the following operations: &lt;ul&gt;<a name="line.53"></a>
<FONT color="green">054</FONT>     * &lt;li&gt;loading the distribution from a file of observed data values&lt;/li&gt;<a name="line.54"></a>
<FONT color="green">055</FONT>     * &lt;li&gt;dividing the input data into "bin ranges" and reporting bin frequency<a name="line.55"></a>
<FONT color="green">056</FONT>     *     counts (data for histogram)&lt;/li&gt;<a name="line.56"></a>
<FONT color="green">057</FONT>     * &lt;li&gt;reporting univariate statistics describing the full set of data values<a name="line.57"></a>
<FONT color="green">058</FONT>     *     as well as the observations within each bin&lt;/li&gt;<a name="line.58"></a>
<FONT color="green">059</FONT>     * &lt;li&gt;generating random values from the distribution&lt;/li&gt;<a name="line.59"></a>
<FONT color="green">060</FONT>     * &lt;/ul&gt;<a name="line.60"></a>
<FONT color="green">061</FONT>     * Applications can use &lt;code&gt;EmpiricalDistribution&lt;/code&gt; to build grouped<a name="line.61"></a>
<FONT color="green">062</FONT>     * frequency histograms representing the input data or to generate random values<a name="line.62"></a>
<FONT color="green">063</FONT>     * "like" those in the input file -- i.e., the values generated will follow the<a name="line.63"></a>
<FONT color="green">064</FONT>     * distribution of the values in the file.&lt;/p&gt;<a name="line.64"></a>
<FONT color="green">065</FONT>     *<a name="line.65"></a>
<FONT color="green">066</FONT>     * &lt;p&gt;The implementation uses what amounts to the<a name="line.66"></a>
<FONT color="green">067</FONT>     * &lt;a href="http://nedwww.ipac.caltech.edu/level5/March02/Silverman/Silver2_6.html"&gt;<a name="line.67"></a>
<FONT color="green">068</FONT>     * Variable Kernel Method&lt;/a&gt; with Gaussian smoothing:&lt;p&gt;<a name="line.68"></a>
<FONT color="green">069</FONT>     * &lt;strong&gt;Digesting the input file&lt;/strong&gt;<a name="line.69"></a>
<FONT color="green">070</FONT>     * &lt;ol&gt;&lt;li&gt;Pass the file once to compute min and max.&lt;/li&gt;<a name="line.70"></a>
<FONT color="green">071</FONT>     * &lt;li&gt;Divide the range from min-max into &lt;code&gt;binCount&lt;/code&gt; "bins."&lt;/li&gt;<a name="line.71"></a>
<FONT color="green">072</FONT>     * &lt;li&gt;Pass the data file again, computing bin counts and univariate<a name="line.72"></a>
<FONT color="green">073</FONT>     *     statistics (mean, std dev.) for each of the bins &lt;/li&gt;<a name="line.73"></a>
<FONT color="green">074</FONT>     * &lt;li&gt;Divide the interval (0,1) into subintervals associated with the bins,<a name="line.74"></a>
<FONT color="green">075</FONT>     *     with the length of a bin's subinterval proportional to its count.&lt;/li&gt;&lt;/ol&gt;<a name="line.75"></a>
<FONT color="green">076</FONT>     * &lt;strong&gt;Generating random values from the distribution&lt;/strong&gt;&lt;ol&gt;<a name="line.76"></a>
<FONT color="green">077</FONT>     * &lt;li&gt;Generate a uniformly distributed value in (0,1) &lt;/li&gt;<a name="line.77"></a>
<FONT color="green">078</FONT>     * &lt;li&gt;Select the subinterval to which the value belongs.<a name="line.78"></a>
<FONT color="green">079</FONT>     * &lt;li&gt;Generate a random Gaussian value with mean = mean of the associated<a name="line.79"></a>
<FONT color="green">080</FONT>     *     bin and std dev = std dev of associated bin.&lt;/li&gt;&lt;/ol&gt;&lt;/p&gt;<a name="line.80"></a>
<FONT color="green">081</FONT>     *<a name="line.81"></a>
<FONT color="green">082</FONT>     * &lt;p&gt;EmpiricalDistribution implements the {@link RealDistribution} interface<a name="line.82"></a>
<FONT color="green">083</FONT>     * as follows.  Given x within the range of values in the dataset, let B<a name="line.83"></a>
<FONT color="green">084</FONT>     * be the bin containing x and let K be the within-bin kernel for B.  Let P(B-)<a name="line.84"></a>
<FONT color="green">085</FONT>     * be the sum of the probabilities of the bins below B and let K(B) be the<a name="line.85"></a>
<FONT color="green">086</FONT>     * mass of B under K (i.e., the integral of the kernel density over B).  Then<a name="line.86"></a>
<FONT color="green">087</FONT>     * set P(X &lt; x) = P(B-) + P(B) * K(x) / K(B) where K(x) is the kernel distribution<a name="line.87"></a>
<FONT color="green">088</FONT>     * evaluated at x. This results in a cdf that matches the grouped frequency<a name="line.88"></a>
<FONT color="green">089</FONT>     * distribution at the bin endpoints and interpolates within bins using<a name="line.89"></a>
<FONT color="green">090</FONT>     * within-bin kernels.&lt;/p&gt;<a name="line.90"></a>
<FONT color="green">091</FONT>     *<a name="line.91"></a>
<FONT color="green">092</FONT>     *&lt;strong&gt;USAGE NOTES:&lt;/strong&gt;&lt;ul&gt;<a name="line.92"></a>
<FONT color="green">093</FONT>     *&lt;li&gt;The &lt;code&gt;binCount&lt;/code&gt; is set by default to 1000.  A good rule of thumb<a name="line.93"></a>
<FONT color="green">094</FONT>     *    is to set the bin count to approximately the length of the input file divided<a name="line.94"></a>
<FONT color="green">095</FONT>     *    by 10. &lt;/li&gt;<a name="line.95"></a>
<FONT color="green">096</FONT>     *&lt;li&gt;The input file &lt;i&gt;must&lt;/i&gt; be a plain text file containing one valid numeric<a name="line.96"></a>
<FONT color="green">097</FONT>     *    entry per line.&lt;/li&gt;<a name="line.97"></a>
<FONT color="green">098</FONT>     * &lt;/ul&gt;&lt;/p&gt;<a name="line.98"></a>
<FONT color="green">099</FONT>     *<a name="line.99"></a>
<FONT color="green">100</FONT>     * @version $Id: EmpiricalDistribution.java 1422350 2012-12-15 20:47:47Z psteitz $<a name="line.100"></a>
<FONT color="green">101</FONT>     */<a name="line.101"></a>
<FONT color="green">102</FONT>    public class EmpiricalDistribution extends AbstractRealDistribution {<a name="line.102"></a>
<FONT color="green">103</FONT>    <a name="line.103"></a>
<FONT color="green">104</FONT>        /** Default bin count */<a name="line.104"></a>
<FONT color="green">105</FONT>        public static final int DEFAULT_BIN_COUNT = 1000;<a name="line.105"></a>
<FONT color="green">106</FONT>    <a name="line.106"></a>
<FONT color="green">107</FONT>        /** Character set for file input */<a name="line.107"></a>
<FONT color="green">108</FONT>        private static final String FILE_CHARSET = "US-ASCII";<a name="line.108"></a>
<FONT color="green">109</FONT>    <a name="line.109"></a>
<FONT color="green">110</FONT>        /** Serializable version identifier */<a name="line.110"></a>
<FONT color="green">111</FONT>        private static final long serialVersionUID = 5729073523949762654L;<a name="line.111"></a>
<FONT color="green">112</FONT>    <a name="line.112"></a>
<FONT color="green">113</FONT>        /** List of SummaryStatistics objects characterizing the bins */<a name="line.113"></a>
<FONT color="green">114</FONT>        private final List&lt;SummaryStatistics&gt; binStats;<a name="line.114"></a>
<FONT color="green">115</FONT>    <a name="line.115"></a>
<FONT color="green">116</FONT>        /** Sample statistics */<a name="line.116"></a>
<FONT color="green">117</FONT>        private SummaryStatistics sampleStats = null;<a name="line.117"></a>
<FONT color="green">118</FONT>    <a name="line.118"></a>
<FONT color="green">119</FONT>        /** Max loaded value */<a name="line.119"></a>
<FONT color="green">120</FONT>        private double max = Double.NEGATIVE_INFINITY;<a name="line.120"></a>
<FONT color="green">121</FONT>    <a name="line.121"></a>
<FONT color="green">122</FONT>        /** Min loaded value */<a name="line.122"></a>
<FONT color="green">123</FONT>        private double min = Double.POSITIVE_INFINITY;<a name="line.123"></a>
<FONT color="green">124</FONT>    <a name="line.124"></a>
<FONT color="green">125</FONT>        /** Grid size */<a name="line.125"></a>
<FONT color="green">126</FONT>        private double delta = 0d;<a name="line.126"></a>
<FONT color="green">127</FONT>    <a name="line.127"></a>
<FONT color="green">128</FONT>        /** number of bins */<a name="line.128"></a>
<FONT color="green">129</FONT>        private final int binCount;<a name="line.129"></a>
<FONT color="green">130</FONT>    <a name="line.130"></a>
<FONT color="green">131</FONT>        /** is the distribution loaded? */<a name="line.131"></a>
<FONT color="green">132</FONT>        private boolean loaded = false;<a name="line.132"></a>
<FONT color="green">133</FONT>    <a name="line.133"></a>
<FONT color="green">134</FONT>        /** upper bounds of subintervals in (0,1) "belonging" to the bins */<a name="line.134"></a>
<FONT color="green">135</FONT>        private double[] upperBounds = null;<a name="line.135"></a>
<FONT color="green">136</FONT>    <a name="line.136"></a>
<FONT color="green">137</FONT>        /** RandomDataGenerator instance to use in repeated calls to getNext() */<a name="line.137"></a>
<FONT color="green">138</FONT>        private final RandomDataGenerator randomData;<a name="line.138"></a>
<FONT color="green">139</FONT>    <a name="line.139"></a>
<FONT color="green">140</FONT>        /**<a name="line.140"></a>
<FONT color="green">141</FONT>         * Creates a new EmpiricalDistribution with the default bin count.<a name="line.141"></a>
<FONT color="green">142</FONT>         */<a name="line.142"></a>
<FONT color="green">143</FONT>        public EmpiricalDistribution() {<a name="line.143"></a>
<FONT color="green">144</FONT>            this(DEFAULT_BIN_COUNT);<a name="line.144"></a>
<FONT color="green">145</FONT>        }<a name="line.145"></a>
<FONT color="green">146</FONT>    <a name="line.146"></a>
<FONT color="green">147</FONT>        /**<a name="line.147"></a>
<FONT color="green">148</FONT>         * Creates a new EmpiricalDistribution with the specified bin count.<a name="line.148"></a>
<FONT color="green">149</FONT>         *<a name="line.149"></a>
<FONT color="green">150</FONT>         * @param binCount number of bins<a name="line.150"></a>
<FONT color="green">151</FONT>         */<a name="line.151"></a>
<FONT color="green">152</FONT>        public EmpiricalDistribution(int binCount) {<a name="line.152"></a>
<FONT color="green">153</FONT>            this(binCount, new RandomDataGenerator());<a name="line.153"></a>
<FONT color="green">154</FONT>        }<a name="line.154"></a>
<FONT color="green">155</FONT>    <a name="line.155"></a>
<FONT color="green">156</FONT>        /**<a name="line.156"></a>
<FONT color="green">157</FONT>         * Creates a new EmpiricalDistribution with the specified bin count using the<a name="line.157"></a>
<FONT color="green">158</FONT>         * provided {@link RandomGenerator} as the source of random data.<a name="line.158"></a>
<FONT color="green">159</FONT>         *<a name="line.159"></a>
<FONT color="green">160</FONT>         * @param binCount number of bins<a name="line.160"></a>
<FONT color="green">161</FONT>         * @param generator random data generator (may be null, resulting in default JDK generator)<a name="line.161"></a>
<FONT color="green">162</FONT>         * @since 3.0<a name="line.162"></a>
<FONT color="green">163</FONT>         */<a name="line.163"></a>
<FONT color="green">164</FONT>        public EmpiricalDistribution(int binCount, RandomGenerator generator) {<a name="line.164"></a>
<FONT color="green">165</FONT>            this(binCount, new RandomDataGenerator(generator));<a name="line.165"></a>
<FONT color="green">166</FONT>        }<a name="line.166"></a>
<FONT color="green">167</FONT>    <a name="line.167"></a>
<FONT color="green">168</FONT>        /**<a name="line.168"></a>
<FONT color="green">169</FONT>         * Creates a new EmpiricalDistribution with default bin count using the<a name="line.169"></a>
<FONT color="green">170</FONT>         * provided {@link RandomGenerator} as the source of random data.<a name="line.170"></a>
<FONT color="green">171</FONT>         *<a name="line.171"></a>
<FONT color="green">172</FONT>         * @param generator random data generator (may be null, resulting in default JDK generator)<a name="line.172"></a>
<FONT color="green">173</FONT>         * @since 3.0<a name="line.173"></a>
<FONT color="green">174</FONT>         */<a name="line.174"></a>
<FONT color="green">175</FONT>        public EmpiricalDistribution(RandomGenerator generator) {<a name="line.175"></a>
<FONT color="green">176</FONT>            this(DEFAULT_BIN_COUNT, generator);<a name="line.176"></a>
<FONT color="green">177</FONT>        }<a name="line.177"></a>
<FONT color="green">178</FONT>    <a name="line.178"></a>
<FONT color="green">179</FONT>        /**<a name="line.179"></a>
<FONT color="green">180</FONT>         * Creates a new EmpiricalDistribution with the specified bin count using the<a name="line.180"></a>
<FONT color="green">181</FONT>         * provided {@link RandomDataImpl} instance as the source of random data.<a name="line.181"></a>
<FONT color="green">182</FONT>         *<a name="line.182"></a>
<FONT color="green">183</FONT>         * @param binCount number of bins<a name="line.183"></a>
<FONT color="green">184</FONT>         * @param randomData random data generator (may be null, resulting in default JDK generator)<a name="line.184"></a>
<FONT color="green">185</FONT>         * @since 3.0<a name="line.185"></a>
<FONT color="green">186</FONT>         * @deprecated As of 3.1. Please use {@link #EmpiricalDistribution(int,RandomGenerator)} instead.<a name="line.186"></a>
<FONT color="green">187</FONT>         */<a name="line.187"></a>
<FONT color="green">188</FONT>        @Deprecated<a name="line.188"></a>
<FONT color="green">189</FONT>        public EmpiricalDistribution(int binCount, RandomDataImpl randomData) {<a name="line.189"></a>
<FONT color="green">190</FONT>            this(binCount, randomData.getDelegate());<a name="line.190"></a>
<FONT color="green">191</FONT>        }<a name="line.191"></a>
<FONT color="green">192</FONT>    <a name="line.192"></a>
<FONT color="green">193</FONT>        /**<a name="line.193"></a>
<FONT color="green">194</FONT>         * Creates a new EmpiricalDistribution with default bin count using the<a name="line.194"></a>
<FONT color="green">195</FONT>         * provided {@link RandomDataImpl} as the source of random data.<a name="line.195"></a>
<FONT color="green">196</FONT>         *<a name="line.196"></a>
<FONT color="green">197</FONT>         * @param randomData random data generator (may be null, resulting in default JDK generator)<a name="line.197"></a>
<FONT color="green">198</FONT>         * @since 3.0<a name="line.198"></a>
<FONT color="green">199</FONT>         * @deprecated As of 3.1. Please use {@link #EmpiricalDistribution(RandomGenerator)} instead.<a name="line.199"></a>
<FONT color="green">200</FONT>         */<a name="line.200"></a>
<FONT color="green">201</FONT>        @Deprecated<a name="line.201"></a>
<FONT color="green">202</FONT>        public EmpiricalDistribution(RandomDataImpl randomData) {<a name="line.202"></a>
<FONT color="green">203</FONT>            this(DEFAULT_BIN_COUNT, randomData);<a name="line.203"></a>
<FONT color="green">204</FONT>        }<a name="line.204"></a>
<FONT color="green">205</FONT>    <a name="line.205"></a>
<FONT color="green">206</FONT>        /**<a name="line.206"></a>
<FONT color="green">207</FONT>         * Private constructor to allow lazy initialisation of the RNG contained<a name="line.207"></a>
<FONT color="green">208</FONT>         * in the {@link #randomData} instance variable.<a name="line.208"></a>
<FONT color="green">209</FONT>         *<a name="line.209"></a>
<FONT color="green">210</FONT>         * @param binCount number of bins<a name="line.210"></a>
<FONT color="green">211</FONT>         * @param randomData Random data generator.<a name="line.211"></a>
<FONT color="green">212</FONT>         */<a name="line.212"></a>
<FONT color="green">213</FONT>        private EmpiricalDistribution(int binCount,<a name="line.213"></a>
<FONT color="green">214</FONT>                                      RandomDataGenerator randomData) {<a name="line.214"></a>
<FONT color="green">215</FONT>            super(null);<a name="line.215"></a>
<FONT color="green">216</FONT>            this.binCount = binCount;<a name="line.216"></a>
<FONT color="green">217</FONT>            this.randomData = randomData;<a name="line.217"></a>
<FONT color="green">218</FONT>            binStats = new ArrayList&lt;SummaryStatistics&gt;();<a name="line.218"></a>
<FONT color="green">219</FONT>        }<a name="line.219"></a>
<FONT color="green">220</FONT>    <a name="line.220"></a>
<FONT color="green">221</FONT>        /**<a name="line.221"></a>
<FONT color="green">222</FONT>         * Computes the empirical distribution from the provided<a name="line.222"></a>
<FONT color="green">223</FONT>         * array of numbers.<a name="line.223"></a>
<FONT color="green">224</FONT>         *<a name="line.224"></a>
<FONT color="green">225</FONT>         * @param in the input data array<a name="line.225"></a>
<FONT color="green">226</FONT>         * @exception NullArgumentException if in is null<a name="line.226"></a>
<FONT color="green">227</FONT>         */<a name="line.227"></a>
<FONT color="green">228</FONT>        public void load(double[] in) throws NullArgumentException {<a name="line.228"></a>
<FONT color="green">229</FONT>            DataAdapter da = new ArrayDataAdapter(in);<a name="line.229"></a>
<FONT color="green">230</FONT>            try {<a name="line.230"></a>
<FONT color="green">231</FONT>                da.computeStats();<a name="line.231"></a>
<FONT color="green">232</FONT>                // new adapter for the second pass<a name="line.232"></a>
<FONT color="green">233</FONT>                fillBinStats(new ArrayDataAdapter(in));<a name="line.233"></a>
<FONT color="green">234</FONT>            } catch (IOException ex) {<a name="line.234"></a>
<FONT color="green">235</FONT>                // Can't happen<a name="line.235"></a>
<FONT color="green">236</FONT>                throw new MathInternalError();<a name="line.236"></a>
<FONT color="green">237</FONT>            }<a name="line.237"></a>
<FONT color="green">238</FONT>            loaded = true;<a name="line.238"></a>
<FONT color="green">239</FONT>    <a name="line.239"></a>
<FONT color="green">240</FONT>        }<a name="line.240"></a>
<FONT color="green">241</FONT>    <a name="line.241"></a>
<FONT color="green">242</FONT>        /**<a name="line.242"></a>
<FONT color="green">243</FONT>         * Computes the empirical distribution using data read from a URL.<a name="line.243"></a>
<FONT color="green">244</FONT>         *<a name="line.244"></a>
<FONT color="green">245</FONT>         * &lt;p&gt;The input file &lt;i&gt;must&lt;/i&gt; be an ASCII text file containing one<a name="line.245"></a>
<FONT color="green">246</FONT>         * valid numeric entry per line.&lt;/p&gt;<a name="line.246"></a>
<FONT color="green">247</FONT>         *<a name="line.247"></a>
<FONT color="green">248</FONT>         * @param url url of the input file<a name="line.248"></a>
<FONT color="green">249</FONT>         *<a name="line.249"></a>
<FONT color="green">250</FONT>         * @throws IOException if an IO error occurs<a name="line.250"></a>
<FONT color="green">251</FONT>         * @throws NullArgumentException if url is null<a name="line.251"></a>
<FONT color="green">252</FONT>         * @throws ZeroException if URL contains no data<a name="line.252"></a>
<FONT color="green">253</FONT>         */<a name="line.253"></a>
<FONT color="green">254</FONT>        public void load(URL url) throws IOException, NullArgumentException, ZeroException {<a name="line.254"></a>
<FONT color="green">255</FONT>            MathUtils.checkNotNull(url);<a name="line.255"></a>
<FONT color="green">256</FONT>            Charset charset = Charset.forName(FILE_CHARSET);<a name="line.256"></a>
<FONT color="green">257</FONT>            BufferedReader in =<a name="line.257"></a>
<FONT color="green">258</FONT>                new BufferedReader(new InputStreamReader(url.openStream(), charset));<a name="line.258"></a>
<FONT color="green">259</FONT>            try {<a name="line.259"></a>
<FONT color="green">260</FONT>                DataAdapter da = new StreamDataAdapter(in);<a name="line.260"></a>
<FONT color="green">261</FONT>                da.computeStats();<a name="line.261"></a>
<FONT color="green">262</FONT>                if (sampleStats.getN() == 0) {<a name="line.262"></a>
<FONT color="green">263</FONT>                    throw new ZeroException(LocalizedFormats.URL_CONTAINS_NO_DATA, url);<a name="line.263"></a>
<FONT color="green">264</FONT>                }<a name="line.264"></a>
<FONT color="green">265</FONT>                // new adapter for the second pass<a name="line.265"></a>
<FONT color="green">266</FONT>                in = new BufferedReader(new InputStreamReader(url.openStream(), charset));<a name="line.266"></a>
<FONT color="green">267</FONT>                fillBinStats(new StreamDataAdapter(in));<a name="line.267"></a>
<FONT color="green">268</FONT>                loaded = true;<a name="line.268"></a>
<FONT color="green">269</FONT>            } finally {<a name="line.269"></a>
<FONT color="green">270</FONT>               try {<a name="line.270"></a>
<FONT color="green">271</FONT>                   in.close();<a name="line.271"></a>
<FONT color="green">272</FONT>               } catch (IOException ex) { //NOPMD<a name="line.272"></a>
<FONT color="green">273</FONT>                   // ignore<a name="line.273"></a>
<FONT color="green">274</FONT>               }<a name="line.274"></a>
<FONT color="green">275</FONT>            }<a name="line.275"></a>
<FONT color="green">276</FONT>        }<a name="line.276"></a>
<FONT color="green">277</FONT>    <a name="line.277"></a>
<FONT color="green">278</FONT>        /**<a name="line.278"></a>
<FONT color="green">279</FONT>         * Computes the empirical distribution from the input file.<a name="line.279"></a>
<FONT color="green">280</FONT>         *<a name="line.280"></a>
<FONT color="green">281</FONT>         * &lt;p&gt;The input file &lt;i&gt;must&lt;/i&gt; be an ASCII text file containing one<a name="line.281"></a>
<FONT color="green">282</FONT>         * valid numeric entry per line.&lt;/p&gt;<a name="line.282"></a>
<FONT color="green">283</FONT>         *<a name="line.283"></a>
<FONT color="green">284</FONT>         * @param file the input file<a name="line.284"></a>
<FONT color="green">285</FONT>         * @throws IOException if an IO error occurs<a name="line.285"></a>
<FONT color="green">286</FONT>         * @throws NullArgumentException if file is null<a name="line.286"></a>
<FONT color="green">287</FONT>         */<a name="line.287"></a>
<FONT color="green">288</FONT>        public void load(File file) throws IOException, NullArgumentException {<a name="line.288"></a>
<FONT color="green">289</FONT>            MathUtils.checkNotNull(file);<a name="line.289"></a>
<FONT color="green">290</FONT>            Charset charset = Charset.forName(FILE_CHARSET);<a name="line.290"></a>
<FONT color="green">291</FONT>            InputStream is = new FileInputStream(file);<a name="line.291"></a>
<FONT color="green">292</FONT>            BufferedReader in = new BufferedReader(new InputStreamReader(is, charset));<a name="line.292"></a>
<FONT color="green">293</FONT>            try {<a name="line.293"></a>
<FONT color="green">294</FONT>                DataAdapter da = new StreamDataAdapter(in);<a name="line.294"></a>
<FONT color="green">295</FONT>                da.computeStats();<a name="line.295"></a>
<FONT color="green">296</FONT>                // new adapter for second pass<a name="line.296"></a>
<FONT color="green">297</FONT>                is = new FileInputStream(file);<a name="line.297"></a>
<FONT color="green">298</FONT>                in = new BufferedReader(new InputStreamReader(is, charset));<a name="line.298"></a>
<FONT color="green">299</FONT>                fillBinStats(new StreamDataAdapter(in));<a name="line.299"></a>
<FONT color="green">300</FONT>                loaded = true;<a name="line.300"></a>
<FONT color="green">301</FONT>            } finally {<a name="line.301"></a>
<FONT color="green">302</FONT>                try {<a name="line.302"></a>
<FONT color="green">303</FONT>                    in.close();<a name="line.303"></a>
<FONT color="green">304</FONT>                } catch (IOException ex) { //NOPMD<a name="line.304"></a>
<FONT color="green">305</FONT>                    // ignore<a name="line.305"></a>
<FONT color="green">306</FONT>                }<a name="line.306"></a>
<FONT color="green">307</FONT>            }<a name="line.307"></a>
<FONT color="green">308</FONT>        }<a name="line.308"></a>
<FONT color="green">309</FONT>    <a name="line.309"></a>
<FONT color="green">310</FONT>        /**<a name="line.310"></a>
<FONT color="green">311</FONT>         * Provides methods for computing &lt;code&gt;sampleStats&lt;/code&gt; and<a name="line.311"></a>
<FONT color="green">312</FONT>         * &lt;code&gt;beanStats&lt;/code&gt; abstracting the source of data.<a name="line.312"></a>
<FONT color="green">313</FONT>         */<a name="line.313"></a>
<FONT color="green">314</FONT>        private abstract class DataAdapter{<a name="line.314"></a>
<FONT color="green">315</FONT>    <a name="line.315"></a>
<FONT color="green">316</FONT>            /**<a name="line.316"></a>
<FONT color="green">317</FONT>             * Compute bin stats.<a name="line.317"></a>
<FONT color="green">318</FONT>             *<a name="line.318"></a>
<FONT color="green">319</FONT>             * @throws IOException  if an error occurs computing bin stats<a name="line.319"></a>
<FONT color="green">320</FONT>             */<a name="line.320"></a>
<FONT color="green">321</FONT>            public abstract void computeBinStats() throws IOException;<a name="line.321"></a>
<FONT color="green">322</FONT>    <a name="line.322"></a>
<FONT color="green">323</FONT>            /**<a name="line.323"></a>
<FONT color="green">324</FONT>             * Compute sample statistics.<a name="line.324"></a>
<FONT color="green">325</FONT>             *<a name="line.325"></a>
<FONT color="green">326</FONT>             * @throws IOException if an error occurs computing sample stats<a name="line.326"></a>
<FONT color="green">327</FONT>             */<a name="line.327"></a>
<FONT color="green">328</FONT>            public abstract void computeStats() throws IOException;<a name="line.328"></a>
<FONT color="green">329</FONT>    <a name="line.329"></a>
<FONT color="green">330</FONT>        }<a name="line.330"></a>
<FONT color="green">331</FONT>    <a name="line.331"></a>
<FONT color="green">332</FONT>        /**<a name="line.332"></a>
<FONT color="green">333</FONT>         * &lt;code&gt;DataAdapter&lt;/code&gt; for data provided through some input stream<a name="line.333"></a>
<FONT color="green">334</FONT>         */<a name="line.334"></a>
<FONT color="green">335</FONT>        private class StreamDataAdapter extends DataAdapter{<a name="line.335"></a>
<FONT color="green">336</FONT>    <a name="line.336"></a>
<FONT color="green">337</FONT>            /** Input stream providing access to the data */<a name="line.337"></a>
<FONT color="green">338</FONT>            private BufferedReader inputStream;<a name="line.338"></a>
<FONT color="green">339</FONT>    <a name="line.339"></a>
<FONT color="green">340</FONT>            /**<a name="line.340"></a>
<FONT color="green">341</FONT>             * Create a StreamDataAdapter from a BufferedReader<a name="line.341"></a>
<FONT color="green">342</FONT>             *<a name="line.342"></a>
<FONT color="green">343</FONT>             * @param in BufferedReader input stream<a name="line.343"></a>
<FONT color="green">344</FONT>             */<a name="line.344"></a>
<FONT color="green">345</FONT>            public StreamDataAdapter(BufferedReader in){<a name="line.345"></a>
<FONT color="green">346</FONT>                super();<a name="line.346"></a>
<FONT color="green">347</FONT>                inputStream = in;<a name="line.347"></a>
<FONT color="green">348</FONT>            }<a name="line.348"></a>
<FONT color="green">349</FONT>    <a name="line.349"></a>
<FONT color="green">350</FONT>            /** {@inheritDoc} */<a name="line.350"></a>
<FONT color="green">351</FONT>            @Override<a name="line.351"></a>
<FONT color="green">352</FONT>            public void computeBinStats() throws IOException {<a name="line.352"></a>
<FONT color="green">353</FONT>                String str = null;<a name="line.353"></a>
<FONT color="green">354</FONT>                double val = 0.0d;<a name="line.354"></a>
<FONT color="green">355</FONT>                while ((str = inputStream.readLine()) != null) {<a name="line.355"></a>
<FONT color="green">356</FONT>                    val = Double.parseDouble(str);<a name="line.356"></a>
<FONT color="green">357</FONT>                    SummaryStatistics stats = binStats.get(findBin(val));<a name="line.357"></a>
<FONT color="green">358</FONT>                    stats.addValue(val);<a name="line.358"></a>
<FONT color="green">359</FONT>                }<a name="line.359"></a>
<FONT color="green">360</FONT>    <a name="line.360"></a>
<FONT color="green">361</FONT>                inputStream.close();<a name="line.361"></a>
<FONT color="green">362</FONT>                inputStream = null;<a name="line.362"></a>
<FONT color="green">363</FONT>            }<a name="line.363"></a>
<FONT color="green">364</FONT>    <a name="line.364"></a>
<FONT color="green">365</FONT>            /** {@inheritDoc} */<a name="line.365"></a>
<FONT color="green">366</FONT>            @Override<a name="line.366"></a>
<FONT color="green">367</FONT>            public void computeStats() throws IOException {<a name="line.367"></a>
<FONT color="green">368</FONT>                String str = null;<a name="line.368"></a>
<FONT color="green">369</FONT>                double val = 0.0;<a name="line.369"></a>
<FONT color="green">370</FONT>                sampleStats = new SummaryStatistics();<a name="line.370"></a>
<FONT color="green">371</FONT>                while ((str = inputStream.readLine()) != null) {<a name="line.371"></a>
<FONT color="green">372</FONT>                    val = Double.valueOf(str).doubleValue();<a name="line.372"></a>
<FONT color="green">373</FONT>                    sampleStats.addValue(val);<a name="line.373"></a>
<FONT color="green">374</FONT>                }<a name="line.374"></a>
<FONT color="green">375</FONT>                inputStream.close();<a name="line.375"></a>
<FONT color="green">376</FONT>                inputStream = null;<a name="line.376"></a>
<FONT color="green">377</FONT>            }<a name="line.377"></a>
<FONT color="green">378</FONT>        }<a name="line.378"></a>
<FONT color="green">379</FONT>    <a name="line.379"></a>
<FONT color="green">380</FONT>        /**<a name="line.380"></a>
<FONT color="green">381</FONT>         * &lt;code&gt;DataAdapter&lt;/code&gt; for data provided as array of doubles.<a name="line.381"></a>
<FONT color="green">382</FONT>         */<a name="line.382"></a>
<FONT color="green">383</FONT>        private class ArrayDataAdapter extends DataAdapter {<a name="line.383"></a>
<FONT color="green">384</FONT>    <a name="line.384"></a>
<FONT color="green">385</FONT>            /** Array of input  data values */<a name="line.385"></a>
<FONT color="green">386</FONT>            private double[] inputArray;<a name="line.386"></a>
<FONT color="green">387</FONT>    <a name="line.387"></a>
<FONT color="green">388</FONT>            /**<a name="line.388"></a>
<FONT color="green">389</FONT>             * Construct an ArrayDataAdapter from a double[] array<a name="line.389"></a>
<FONT color="green">390</FONT>             *<a name="line.390"></a>
<FONT color="green">391</FONT>             * @param in double[] array holding the data<a name="line.391"></a>
<FONT color="green">392</FONT>             * @throws NullArgumentException if in is null<a name="line.392"></a>
<FONT color="green">393</FONT>             */<a name="line.393"></a>
<FONT color="green">394</FONT>            public ArrayDataAdapter(double[] in) throws NullArgumentException {<a name="line.394"></a>
<FONT color="green">395</FONT>                super();<a name="line.395"></a>
<FONT color="green">396</FONT>                MathUtils.checkNotNull(in);<a name="line.396"></a>
<FONT color="green">397</FONT>                inputArray = in;<a name="line.397"></a>
<FONT color="green">398</FONT>            }<a name="line.398"></a>
<FONT color="green">399</FONT>    <a name="line.399"></a>
<FONT color="green">400</FONT>            /** {@inheritDoc} */<a name="line.400"></a>
<FONT color="green">401</FONT>            @Override<a name="line.401"></a>
<FONT color="green">402</FONT>            public void computeStats() throws IOException {<a name="line.402"></a>
<FONT color="green">403</FONT>                sampleStats = new SummaryStatistics();<a name="line.403"></a>
<FONT color="green">404</FONT>                for (int i = 0; i &lt; inputArray.length; i++) {<a name="line.404"></a>
<FONT color="green">405</FONT>                    sampleStats.addValue(inputArray[i]);<a name="line.405"></a>
<FONT color="green">406</FONT>                }<a name="line.406"></a>
<FONT color="green">407</FONT>            }<a name="line.407"></a>
<FONT color="green">408</FONT>    <a name="line.408"></a>
<FONT color="green">409</FONT>            /** {@inheritDoc} */<a name="line.409"></a>
<FONT color="green">410</FONT>            @Override<a name="line.410"></a>
<FONT color="green">411</FONT>            public void computeBinStats() throws IOException {<a name="line.411"></a>
<FONT color="green">412</FONT>                for (int i = 0; i &lt; inputArray.length; i++) {<a name="line.412"></a>
<FONT color="green">413</FONT>                    SummaryStatistics stats =<a name="line.413"></a>
<FONT color="green">414</FONT>                        binStats.get(findBin(inputArray[i]));<a name="line.414"></a>
<FONT color="green">415</FONT>                    stats.addValue(inputArray[i]);<a name="line.415"></a>
<FONT color="green">416</FONT>                }<a name="line.416"></a>
<FONT color="green">417</FONT>            }<a name="line.417"></a>
<FONT color="green">418</FONT>        }<a name="line.418"></a>
<FONT color="green">419</FONT>    <a name="line.419"></a>
<FONT color="green">420</FONT>        /**<a name="line.420"></a>
<FONT color="green">421</FONT>         * Fills binStats array (second pass through data file).<a name="line.421"></a>
<FONT color="green">422</FONT>         *<a name="line.422"></a>
<FONT color="green">423</FONT>         * @param da object providing access to the data<a name="line.423"></a>
<FONT color="green">424</FONT>         * @throws IOException  if an IO error occurs<a name="line.424"></a>
<FONT color="green">425</FONT>         */<a name="line.425"></a>
<FONT color="green">426</FONT>        private void fillBinStats(final DataAdapter da)<a name="line.426"></a>
<FONT color="green">427</FONT>            throws IOException {<a name="line.427"></a>
<FONT color="green">428</FONT>            // Set up grid<a name="line.428"></a>
<FONT color="green">429</FONT>            min = sampleStats.getMin();<a name="line.429"></a>
<FONT color="green">430</FONT>            max = sampleStats.getMax();<a name="line.430"></a>
<FONT color="green">431</FONT>            delta = (max - min)/(Double.valueOf(binCount)).doubleValue();<a name="line.431"></a>
<FONT color="green">432</FONT>    <a name="line.432"></a>
<FONT color="green">433</FONT>            // Initialize binStats ArrayList<a name="line.433"></a>
<FONT color="green">434</FONT>            if (!binStats.isEmpty()) {<a name="line.434"></a>
<FONT color="green">435</FONT>                binStats.clear();<a name="line.435"></a>
<FONT color="green">436</FONT>            }<a name="line.436"></a>
<FONT color="green">437</FONT>            for (int i = 0; i &lt; binCount; i++) {<a name="line.437"></a>
<FONT color="green">438</FONT>                SummaryStatistics stats = new SummaryStatistics();<a name="line.438"></a>
<FONT color="green">439</FONT>                binStats.add(i,stats);<a name="line.439"></a>
<FONT color="green">440</FONT>            }<a name="line.440"></a>
<FONT color="green">441</FONT>    <a name="line.441"></a>
<FONT color="green">442</FONT>            // Filling data in binStats Array<a name="line.442"></a>
<FONT color="green">443</FONT>            da.computeBinStats();<a name="line.443"></a>
<FONT color="green">444</FONT>    <a name="line.444"></a>
<FONT color="green">445</FONT>            // Assign upperBounds based on bin counts<a name="line.445"></a>
<FONT color="green">446</FONT>            upperBounds = new double[binCount];<a name="line.446"></a>
<FONT color="green">447</FONT>            upperBounds[0] =<a name="line.447"></a>
<FONT color="green">448</FONT>            ((double) binStats.get(0).getN()) / (double) sampleStats.getN();<a name="line.448"></a>
<FONT color="green">449</FONT>            for (int i = 1; i &lt; binCount-1; i++) {<a name="line.449"></a>
<FONT color="green">450</FONT>                upperBounds[i] = upperBounds[i-1] +<a name="line.450"></a>
<FONT color="green">451</FONT>                ((double) binStats.get(i).getN()) / (double) sampleStats.getN();<a name="line.451"></a>
<FONT color="green">452</FONT>            }<a name="line.452"></a>
<FONT color="green">453</FONT>            upperBounds[binCount-1] = 1.0d;<a name="line.453"></a>
<FONT color="green">454</FONT>        }<a name="line.454"></a>
<FONT color="green">455</FONT>    <a name="line.455"></a>
<FONT color="green">456</FONT>        /**<a name="line.456"></a>
<FONT color="green">457</FONT>         * Returns the index of the bin to which the given value belongs<a name="line.457"></a>
<FONT color="green">458</FONT>         *<a name="line.458"></a>
<FONT color="green">459</FONT>         * @param value  the value whose bin we are trying to find<a name="line.459"></a>
<FONT color="green">460</FONT>         * @return the index of the bin containing the value<a name="line.460"></a>
<FONT color="green">461</FONT>         */<a name="line.461"></a>
<FONT color="green">462</FONT>        private int findBin(double value) {<a name="line.462"></a>
<FONT color="green">463</FONT>            return FastMath.min(<a name="line.463"></a>
<FONT color="green">464</FONT>                    FastMath.max((int) FastMath.ceil((value - min) / delta) - 1, 0),<a name="line.464"></a>
<FONT color="green">465</FONT>                    binCount - 1);<a name="line.465"></a>
<FONT color="green">466</FONT>        }<a name="line.466"></a>
<FONT color="green">467</FONT>    <a name="line.467"></a>
<FONT color="green">468</FONT>        /**<a name="line.468"></a>
<FONT color="green">469</FONT>         * Generates a random value from this distribution.<a name="line.469"></a>
<FONT color="green">470</FONT>         * &lt;strong&gt;Preconditions:&lt;/strong&gt;&lt;ul&gt;<a name="line.470"></a>
<FONT color="green">471</FONT>         * &lt;li&gt;the distribution must be loaded before invoking this method&lt;/li&gt;&lt;/ul&gt;<a name="line.471"></a>
<FONT color="green">472</FONT>         * @return the random value.<a name="line.472"></a>
<FONT color="green">473</FONT>         * @throws MathIllegalStateException if the distribution has not been loaded<a name="line.473"></a>
<FONT color="green">474</FONT>         */<a name="line.474"></a>
<FONT color="green">475</FONT>        public double getNextValue() throws MathIllegalStateException {<a name="line.475"></a>
<FONT color="green">476</FONT>    <a name="line.476"></a>
<FONT color="green">477</FONT>            if (!loaded) {<a name="line.477"></a>
<FONT color="green">478</FONT>                throw new MathIllegalStateException(LocalizedFormats.DISTRIBUTION_NOT_LOADED);<a name="line.478"></a>
<FONT color="green">479</FONT>            }<a name="line.479"></a>
<FONT color="green">480</FONT>    <a name="line.480"></a>
<FONT color="green">481</FONT>            // Start with a uniformly distributed random number in (0,1)<a name="line.481"></a>
<FONT color="green">482</FONT>            final double x = randomData.nextUniform(0,1);<a name="line.482"></a>
<FONT color="green">483</FONT>    <a name="line.483"></a>
<FONT color="green">484</FONT>            // Use this to select the bin and generate a Gaussian within the bin<a name="line.484"></a>
<FONT color="green">485</FONT>            for (int i = 0; i &lt; binCount; i++) {<a name="line.485"></a>
<FONT color="green">486</FONT>               if (x &lt;= upperBounds[i]) {<a name="line.486"></a>
<FONT color="green">487</FONT>                   SummaryStatistics stats = binStats.get(i);<a name="line.487"></a>
<FONT color="green">488</FONT>                   if (stats.getN() &gt; 0) {<a name="line.488"></a>
<FONT color="green">489</FONT>                       if (stats.getStandardDeviation() &gt; 0) {  // more than one obs<a name="line.489"></a>
<FONT color="green">490</FONT>                           return randomData.nextGaussian(stats.getMean(),<a name="line.490"></a>
<FONT color="green">491</FONT>                                                          stats.getStandardDeviation());<a name="line.491"></a>
<FONT color="green">492</FONT>                       } else {<a name="line.492"></a>
<FONT color="green">493</FONT>                           return stats.getMean(); // only one obs in bin<a name="line.493"></a>
<FONT color="green">494</FONT>                       }<a name="line.494"></a>
<FONT color="green">495</FONT>                   }<a name="line.495"></a>
<FONT color="green">496</FONT>               }<a name="line.496"></a>
<FONT color="green">497</FONT>            }<a name="line.497"></a>
<FONT color="green">498</FONT>            throw new MathIllegalStateException(LocalizedFormats.NO_BIN_SELECTED);<a name="line.498"></a>
<FONT color="green">499</FONT>        }<a name="line.499"></a>
<FONT color="green">500</FONT>    <a name="line.500"></a>
<FONT color="green">501</FONT>        /**<a name="line.501"></a>
<FONT color="green">502</FONT>         * Returns a {@link StatisticalSummary} describing this distribution.<a name="line.502"></a>
<FONT color="green">503</FONT>         * &lt;strong&gt;Preconditions:&lt;/strong&gt;&lt;ul&gt;<a name="line.503"></a>
<FONT color="green">504</FONT>         * &lt;li&gt;the distribution must be loaded before invoking this method&lt;/li&gt;&lt;/ul&gt;<a name="line.504"></a>
<FONT color="green">505</FONT>         *<a name="line.505"></a>
<FONT color="green">506</FONT>         * @return the sample statistics<a name="line.506"></a>
<FONT color="green">507</FONT>         * @throws IllegalStateException if the distribution has not been loaded<a name="line.507"></a>
<FONT color="green">508</FONT>         */<a name="line.508"></a>
<FONT color="green">509</FONT>        public StatisticalSummary getSampleStats() {<a name="line.509"></a>
<FONT color="green">510</FONT>            return sampleStats;<a name="line.510"></a>
<FONT color="green">511</FONT>        }<a name="line.511"></a>
<FONT color="green">512</FONT>    <a name="line.512"></a>
<FONT color="green">513</FONT>        /**<a name="line.513"></a>
<FONT color="green">514</FONT>         * Returns the number of bins.<a name="line.514"></a>
<FONT color="green">515</FONT>         *<a name="line.515"></a>
<FONT color="green">516</FONT>         * @return the number of bins.<a name="line.516"></a>
<FONT color="green">517</FONT>         */<a name="line.517"></a>
<FONT color="green">518</FONT>        public int getBinCount() {<a name="line.518"></a>
<FONT color="green">519</FONT>            return binCount;<a name="line.519"></a>
<FONT color="green">520</FONT>        }<a name="line.520"></a>
<FONT color="green">521</FONT>    <a name="line.521"></a>
<FONT color="green">522</FONT>        /**<a name="line.522"></a>
<FONT color="green">523</FONT>         * Returns a List of {@link SummaryStatistics} instances containing<a name="line.523"></a>
<FONT color="green">524</FONT>         * statistics describing the values in each of the bins.  The list is<a name="line.524"></a>
<FONT color="green">525</FONT>         * indexed on the bin number.<a name="line.525"></a>
<FONT color="green">526</FONT>         *<a name="line.526"></a>
<FONT color="green">527</FONT>         * @return List of bin statistics.<a name="line.527"></a>
<FONT color="green">528</FONT>         */<a name="line.528"></a>
<FONT color="green">529</FONT>        public List&lt;SummaryStatistics&gt; getBinStats() {<a name="line.529"></a>
<FONT color="green">530</FONT>            return binStats;<a name="line.530"></a>
<FONT color="green">531</FONT>        }<a name="line.531"></a>
<FONT color="green">532</FONT>    <a name="line.532"></a>
<FONT color="green">533</FONT>        /**<a name="line.533"></a>
<FONT color="green">534</FONT>         * &lt;p&gt;Returns a fresh copy of the array of upper bounds for the bins.<a name="line.534"></a>
<FONT color="green">535</FONT>         * Bins are: &lt;br/&gt;<a name="line.535"></a>
<FONT color="green">536</FONT>         * [min,upperBounds[0]],(upperBounds[0],upperBounds[1]],...,<a name="line.536"></a>
<FONT color="green">537</FONT>         *  (upperBounds[binCount-2], upperBounds[binCount-1] = max].&lt;/p&gt;<a name="line.537"></a>
<FONT color="green">538</FONT>         *<a name="line.538"></a>
<FONT color="green">539</FONT>         * &lt;p&gt;Note: In versions 1.0-2.0 of commons-math, this method<a name="line.539"></a>
<FONT color="green">540</FONT>         * incorrectly returned the array of probability generator upper<a name="line.540"></a>
<FONT color="green">541</FONT>         * bounds now returned by {@link #getGeneratorUpperBounds()}.&lt;/p&gt;<a name="line.541"></a>
<FONT color="green">542</FONT>         *<a name="line.542"></a>
<FONT color="green">543</FONT>         * @return array of bin upper bounds<a name="line.543"></a>
<FONT color="green">544</FONT>         * @since 2.1<a name="line.544"></a>
<FONT color="green">545</FONT>         */<a name="line.545"></a>
<FONT color="green">546</FONT>        public double[] getUpperBounds() {<a name="line.546"></a>
<FONT color="green">547</FONT>            double[] binUpperBounds = new double[binCount];<a name="line.547"></a>
<FONT color="green">548</FONT>            for (int i = 0; i &lt; binCount - 1; i++) {<a name="line.548"></a>
<FONT color="green">549</FONT>                binUpperBounds[i] = min + delta * (i + 1);<a name="line.549"></a>
<FONT color="green">550</FONT>            }<a name="line.550"></a>
<FONT color="green">551</FONT>            binUpperBounds[binCount - 1] = max;<a name="line.551"></a>
<FONT color="green">552</FONT>            return binUpperBounds;<a name="line.552"></a>
<FONT color="green">553</FONT>        }<a name="line.553"></a>
<FONT color="green">554</FONT>    <a name="line.554"></a>
<FONT color="green">555</FONT>        /**<a name="line.555"></a>
<FONT color="green">556</FONT>         * &lt;p&gt;Returns a fresh copy of the array of upper bounds of the subintervals<a name="line.556"></a>
<FONT color="green">557</FONT>         * of [0,1] used in generating data from the empirical distribution.<a name="line.557"></a>
<FONT color="green">558</FONT>         * Subintervals correspond to bins with lengths proportional to bin counts.&lt;/p&gt;<a name="line.558"></a>
<FONT color="green">559</FONT>         *<a name="line.559"></a>
<FONT color="green">560</FONT>         * &lt;p&gt;In versions 1.0-2.0 of commons-math, this array was (incorrectly) returned<a name="line.560"></a>
<FONT color="green">561</FONT>         * by {@link #getUpperBounds()}.&lt;/p&gt;<a name="line.561"></a>
<FONT color="green">562</FONT>         *<a name="line.562"></a>
<FONT color="green">563</FONT>         * @since 2.1<a name="line.563"></a>
<FONT color="green">564</FONT>         * @return array of upper bounds of subintervals used in data generation<a name="line.564"></a>
<FONT color="green">565</FONT>         */<a name="line.565"></a>
<FONT color="green">566</FONT>        public double[] getGeneratorUpperBounds() {<a name="line.566"></a>
<FONT color="green">567</FONT>            int len = upperBounds.length;<a name="line.567"></a>
<FONT color="green">568</FONT>            double[] out = new double[len];<a name="line.568"></a>
<FONT color="green">569</FONT>            System.arraycopy(upperBounds, 0, out, 0, len);<a name="line.569"></a>
<FONT color="green">570</FONT>            return out;<a name="line.570"></a>
<FONT color="green">571</FONT>        }<a name="line.571"></a>
<FONT color="green">572</FONT>    <a name="line.572"></a>
<FONT color="green">573</FONT>        /**<a name="line.573"></a>
<FONT color="green">574</FONT>         * Property indicating whether or not the distribution has been loaded.<a name="line.574"></a>
<FONT color="green">575</FONT>         *<a name="line.575"></a>
<FONT color="green">576</FONT>         * @return true if the distribution has been loaded<a name="line.576"></a>
<FONT color="green">577</FONT>         */<a name="line.577"></a>
<FONT color="green">578</FONT>        public boolean isLoaded() {<a name="line.578"></a>
<FONT color="green">579</FONT>            return loaded;<a name="line.579"></a>
<FONT color="green">580</FONT>        }<a name="line.580"></a>
<FONT color="green">581</FONT>    <a name="line.581"></a>
<FONT color="green">582</FONT>        /**<a name="line.582"></a>
<FONT color="green">583</FONT>         * Reseeds the random number generator used by {@link #getNextValue()}.<a name="line.583"></a>
<FONT color="green">584</FONT>         *<a name="line.584"></a>
<FONT color="green">585</FONT>         * @param seed random generator seed<a name="line.585"></a>
<FONT color="green">586</FONT>         * @since 3.0<a name="line.586"></a>
<FONT color="green">587</FONT>         */<a name="line.587"></a>
<FONT color="green">588</FONT>        public void reSeed(long seed) {<a name="line.588"></a>
<FONT color="green">589</FONT>            randomData.reSeed(seed);<a name="line.589"></a>
<FONT color="green">590</FONT>        }<a name="line.590"></a>
<FONT color="green">591</FONT>    <a name="line.591"></a>
<FONT color="green">592</FONT>        // Distribution methods ---------------------------<a name="line.592"></a>
<FONT color="green">593</FONT>    <a name="line.593"></a>
<FONT color="green">594</FONT>        /**<a name="line.594"></a>
<FONT color="green">595</FONT>         * {@inheritDoc}<a name="line.595"></a>
<FONT color="green">596</FONT>         * @since 3.1<a name="line.596"></a>
<FONT color="green">597</FONT>         */<a name="line.597"></a>
<FONT color="green">598</FONT>        public double probability(double x) {<a name="line.598"></a>
<FONT color="green">599</FONT>            return 0;<a name="line.599"></a>
<FONT color="green">600</FONT>        }<a name="line.600"></a>
<FONT color="green">601</FONT>    <a name="line.601"></a>
<FONT color="green">602</FONT>        /**<a name="line.602"></a>
<FONT color="green">603</FONT>         * {@inheritDoc}<a name="line.603"></a>
<FONT color="green">604</FONT>         *<a name="line.604"></a>
<FONT color="green">605</FONT>         * &lt;p&gt;Returns the kernel density normalized so that its integral over each bin<a name="line.605"></a>
<FONT color="green">606</FONT>         * equals the bin mass.&lt;/p&gt;<a name="line.606"></a>
<FONT color="green">607</FONT>         *<a name="line.607"></a>
<FONT color="green">608</FONT>         * &lt;p&gt;Algorithm description: &lt;ol&gt;<a name="line.608"></a>
<FONT color="green">609</FONT>         * &lt;li&gt;Find the bin B that x belongs to.&lt;/li&gt;<a name="line.609"></a>
<FONT color="green">610</FONT>         * &lt;li&gt;Compute K(B) = the mass of B with respect to the within-bin kernel (i.e., the<a name="line.610"></a>
<FONT color="green">611</FONT>         * integral of the kernel density over B).&lt;/li&gt;<a name="line.611"></a>
<FONT color="green">612</FONT>         * &lt;li&gt;Return k(x) * P(B) / K(B), where k is the within-bin kernel density<a name="line.612"></a>
<FONT color="green">613</FONT>         * and P(B) is the mass of B.&lt;/li&gt;&lt;/ol&gt;&lt;/p&gt;<a name="line.613"></a>
<FONT color="green">614</FONT>         * @since 3.1<a name="line.614"></a>
<FONT color="green">615</FONT>         */<a name="line.615"></a>
<FONT color="green">616</FONT>        public double density(double x) {<a name="line.616"></a>
<FONT color="green">617</FONT>            if (x &lt; min || x &gt; max) {<a name="line.617"></a>
<FONT color="green">618</FONT>                return 0d;<a name="line.618"></a>
<FONT color="green">619</FONT>            }<a name="line.619"></a>
<FONT color="green">620</FONT>            final int binIndex = findBin(x);<a name="line.620"></a>
<FONT color="green">621</FONT>            final RealDistribution kernel = getKernel(binStats.get(binIndex));<a name="line.621"></a>
<FONT color="green">622</FONT>            return kernel.density(x) * pB(binIndex) / kB(binIndex);<a name="line.622"></a>
<FONT color="green">623</FONT>        }<a name="line.623"></a>
<FONT color="green">624</FONT>    <a name="line.624"></a>
<FONT color="green">625</FONT>        /**<a name="line.625"></a>
<FONT color="green">626</FONT>         * {@inheritDoc}<a name="line.626"></a>
<FONT color="green">627</FONT>         *<a name="line.627"></a>
<FONT color="green">628</FONT>         * &lt;p&gt;Algorithm description:&lt;ol&gt;<a name="line.628"></a>
<FONT color="green">629</FONT>         * &lt;li&gt;Find the bin B that x belongs to.&lt;/li&gt;<a name="line.629"></a>
<FONT color="green">630</FONT>         * &lt;li&gt;Compute P(B) = the mass of B and P(B-) = the combined mass of the bins below B.&lt;/li&gt;<a name="line.630"></a>
<FONT color="green">631</FONT>         * &lt;li&gt;Compute K(B) = the probability mass of B with respect to the within-bin kernel<a name="line.631"></a>
<FONT color="green">632</FONT>         * and K(B-) = the kernel distribution evaluated at the lower endpoint of B&lt;/li&gt;<a name="line.632"></a>
<FONT color="green">633</FONT>         * &lt;li&gt;Return P(B-) + P(B) * [K(x) - K(B-)] / K(B) where<a name="line.633"></a>
<FONT color="green">634</FONT>         * K(x) is the within-bin kernel distribution function evaluated at x.&lt;/li&gt;&lt;/ol&gt;&lt;/p&gt;<a name="line.634"></a>
<FONT color="green">635</FONT>         *<a name="line.635"></a>
<FONT color="green">636</FONT>         * @since 3.1<a name="line.636"></a>
<FONT color="green">637</FONT>         */<a name="line.637"></a>
<FONT color="green">638</FONT>        public double cumulativeProbability(double x) {<a name="line.638"></a>
<FONT color="green">639</FONT>            if (x &lt; min) {<a name="line.639"></a>
<FONT color="green">640</FONT>                return 0d;<a name="line.640"></a>
<FONT color="green">641</FONT>            } else if (x &gt;= max) {<a name="line.641"></a>
<FONT color="green">642</FONT>                return 1d;<a name="line.642"></a>
<FONT color="green">643</FONT>            }<a name="line.643"></a>
<FONT color="green">644</FONT>            final int binIndex = findBin(x);<a name="line.644"></a>
<FONT color="green">645</FONT>            final double pBminus = pBminus(binIndex);<a name="line.645"></a>
<FONT color="green">646</FONT>            final double pB = pB(binIndex);<a name="line.646"></a>
<FONT color="green">647</FONT>            final double[] binBounds = getUpperBounds();<a name="line.647"></a>
<FONT color="green">648</FONT>            final double kB = kB(binIndex);<a name="line.648"></a>
<FONT color="green">649</FONT>            final double lower = binIndex == 0 ? min : binBounds[binIndex - 1];<a name="line.649"></a>
<FONT color="green">650</FONT>            final RealDistribution kernel = k(x);<a name="line.650"></a>
<FONT color="green">651</FONT>            final double withinBinCum =<a name="line.651"></a>
<FONT color="green">652</FONT>                (kernel.cumulativeProbability(x) -  kernel.cumulativeProbability(lower)) / kB;<a name="line.652"></a>
<FONT color="green">653</FONT>            return pBminus + pB * withinBinCum;<a name="line.653"></a>
<FONT color="green">654</FONT>        }<a name="line.654"></a>
<FONT color="green">655</FONT>    <a name="line.655"></a>
<FONT color="green">656</FONT>        /**<a name="line.656"></a>
<FONT color="green">657</FONT>         * {@inheritDoc}<a name="line.657"></a>
<FONT color="green">658</FONT>         *<a name="line.658"></a>
<FONT color="green">659</FONT>         * &lt;p&gt;Algorithm description:&lt;ol&gt;<a name="line.659"></a>
<FONT color="green">660</FONT>         * &lt;li&gt;Find the smallest i such that the sum of the masses of the bins<a name="line.660"></a>
<FONT color="green">661</FONT>         *  through i is at least p.&lt;/li&gt;<a name="line.661"></a>
<FONT color="green">662</FONT>         * &lt;li&gt;<a name="line.662"></a>
<FONT color="green">663</FONT>         *   Let K be the within-bin kernel distribution for bin i.&lt;/br&gt;<a name="line.663"></a>
<FONT color="green">664</FONT>         *   Let K(B) be the mass of B under K. &lt;br/&gt;<a name="line.664"></a>
<FONT color="green">665</FONT>         *   Let K(B-) be K evaluated at the lower endpoint of B (the combined<a name="line.665"></a>
<FONT color="green">666</FONT>         *   mass of the bins below B under K).&lt;br/&gt;<a name="line.666"></a>
<FONT color="green">667</FONT>         *   Let P(B) be the probability of bin i.&lt;br/&gt;<a name="line.667"></a>
<FONT color="green">668</FONT>         *   Let P(B-) be the sum of the bin masses below bin i. &lt;br/&gt;<a name="line.668"></a>
<FONT color="green">669</FONT>         *   Let pCrit = p - P(B-)&lt;br/&gt;<a name="line.669"></a>
<FONT color="green">670</FONT>         * &lt;li&gt;Return the inverse of K evaluated at &lt;br/&gt;<a name="line.670"></a>
<FONT color="green">671</FONT>         *    K(B-) + pCrit * K(B) / P(B) &lt;/li&gt;<a name="line.671"></a>
<FONT color="green">672</FONT>         *  &lt;/ol&gt;&lt;/p&gt;<a name="line.672"></a>
<FONT color="green">673</FONT>         *<a name="line.673"></a>
<FONT color="green">674</FONT>         * @since 3.1<a name="line.674"></a>
<FONT color="green">675</FONT>         */<a name="line.675"></a>
<FONT color="green">676</FONT>        public double inverseCumulativeProbability(final double p) throws OutOfRangeException {<a name="line.676"></a>
<FONT color="green">677</FONT>            if (p &lt; 0.0 || p &gt; 1.0) {<a name="line.677"></a>
<FONT color="green">678</FONT>                throw new OutOfRangeException(p, 0, 1);<a name="line.678"></a>
<FONT color="green">679</FONT>            }<a name="line.679"></a>
<FONT color="green">680</FONT>    <a name="line.680"></a>
<FONT color="green">681</FONT>            if (p == 0.0) {<a name="line.681"></a>
<FONT color="green">682</FONT>                return getSupportLowerBound();<a name="line.682"></a>
<FONT color="green">683</FONT>            }<a name="line.683"></a>
<FONT color="green">684</FONT>    <a name="line.684"></a>
<FONT color="green">685</FONT>            if (p == 1.0) {<a name="line.685"></a>
<FONT color="green">686</FONT>                return getSupportUpperBound();<a name="line.686"></a>
<FONT color="green">687</FONT>            }<a name="line.687"></a>
<FONT color="green">688</FONT>    <a name="line.688"></a>
<FONT color="green">689</FONT>            int i = 0;<a name="line.689"></a>
<FONT color="green">690</FONT>            while (cumBinP(i) &lt; p) {<a name="line.690"></a>
<FONT color="green">691</FONT>                i++;<a name="line.691"></a>
<FONT color="green">692</FONT>            }<a name="line.692"></a>
<FONT color="green">693</FONT>    <a name="line.693"></a>
<FONT color="green">694</FONT>            final RealDistribution kernel = getKernel(binStats.get(i));<a name="line.694"></a>
<FONT color="green">695</FONT>            final double kB = kB(i);<a name="line.695"></a>
<FONT color="green">696</FONT>            final double[] binBounds = getUpperBounds();<a name="line.696"></a>
<FONT color="green">697</FONT>            final double lower = i == 0 ? min : binBounds[i - 1];<a name="line.697"></a>
<FONT color="green">698</FONT>            final double kBminus = kernel.cumulativeProbability(lower);<a name="line.698"></a>
<FONT color="green">699</FONT>            final double pB = pB(i);<a name="line.699"></a>
<FONT color="green">700</FONT>            final double pBminus = pBminus(i);<a name="line.700"></a>
<FONT color="green">701</FONT>            final double pCrit = p - pBminus;<a name="line.701"></a>
<FONT color="green">702</FONT>            if (pCrit &lt;= 0) {<a name="line.702"></a>
<FONT color="green">703</FONT>                return lower;<a name="line.703"></a>
<FONT color="green">704</FONT>            }<a name="line.704"></a>
<FONT color="green">705</FONT>            return kernel.inverseCumulativeProbability(kBminus + pCrit * kB / pB);<a name="line.705"></a>
<FONT color="green">706</FONT>        }<a name="line.706"></a>
<FONT color="green">707</FONT>    <a name="line.707"></a>
<FONT color="green">708</FONT>        /**<a name="line.708"></a>
<FONT color="green">709</FONT>         * {@inheritDoc}<a name="line.709"></a>
<FONT color="green">710</FONT>         * @since 3.1<a name="line.710"></a>
<FONT color="green">711</FONT>         */<a name="line.711"></a>
<FONT color="green">712</FONT>        public double getNumericalMean() {<a name="line.712"></a>
<FONT color="green">713</FONT>           return sampleStats.getMean();<a name="line.713"></a>
<FONT color="green">714</FONT>        }<a name="line.714"></a>
<FONT color="green">715</FONT>    <a name="line.715"></a>
<FONT color="green">716</FONT>        /**<a name="line.716"></a>
<FONT color="green">717</FONT>         * {@inheritDoc}<a name="line.717"></a>
<FONT color="green">718</FONT>         * @since 3.1<a name="line.718"></a>
<FONT color="green">719</FONT>         */<a name="line.719"></a>
<FONT color="green">720</FONT>        public double getNumericalVariance() {<a name="line.720"></a>
<FONT color="green">721</FONT>            return sampleStats.getVariance();<a name="line.721"></a>
<FONT color="green">722</FONT>        }<a name="line.722"></a>
<FONT color="green">723</FONT>    <a name="line.723"></a>
<FONT color="green">724</FONT>        /**<a name="line.724"></a>
<FONT color="green">725</FONT>         * {@inheritDoc}<a name="line.725"></a>
<FONT color="green">726</FONT>         * @since 3.1<a name="line.726"></a>
<FONT color="green">727</FONT>         */<a name="line.727"></a>
<FONT color="green">728</FONT>        public double getSupportLowerBound() {<a name="line.728"></a>
<FONT color="green">729</FONT>           return min;<a name="line.729"></a>
<FONT color="green">730</FONT>        }<a name="line.730"></a>
<FONT color="green">731</FONT>    <a name="line.731"></a>
<FONT color="green">732</FONT>        /**<a name="line.732"></a>
<FONT color="green">733</FONT>         * {@inheritDoc}<a name="line.733"></a>
<FONT color="green">734</FONT>         * @since 3.1<a name="line.734"></a>
<FONT color="green">735</FONT>         */<a name="line.735"></a>
<FONT color="green">736</FONT>        public double getSupportUpperBound() {<a name="line.736"></a>
<FONT color="green">737</FONT>            return max;<a name="line.737"></a>
<FONT color="green">738</FONT>        }<a name="line.738"></a>
<FONT color="green">739</FONT>    <a name="line.739"></a>
<FONT color="green">740</FONT>        /**<a name="line.740"></a>
<FONT color="green">741</FONT>         * {@inheritDoc}<a name="line.741"></a>
<FONT color="green">742</FONT>         * @since 3.1<a name="line.742"></a>
<FONT color="green">743</FONT>         */<a name="line.743"></a>
<FONT color="green">744</FONT>        public boolean isSupportLowerBoundInclusive() {<a name="line.744"></a>
<FONT color="green">745</FONT>            return true;<a name="line.745"></a>
<FONT color="green">746</FONT>        }<a name="line.746"></a>
<FONT color="green">747</FONT>    <a name="line.747"></a>
<FONT color="green">748</FONT>        /**<a name="line.748"></a>
<FONT color="green">749</FONT>         * {@inheritDoc}<a name="line.749"></a>
<FONT color="green">750</FONT>         * @since 3.1<a name="line.750"></a>
<FONT color="green">751</FONT>         */<a name="line.751"></a>
<FONT color="green">752</FONT>        public boolean isSupportUpperBoundInclusive() {<a name="line.752"></a>
<FONT color="green">753</FONT>            return true;<a name="line.753"></a>
<FONT color="green">754</FONT>        }<a name="line.754"></a>
<FONT color="green">755</FONT>    <a name="line.755"></a>
<FONT color="green">756</FONT>        /**<a name="line.756"></a>
<FONT color="green">757</FONT>         * {@inheritDoc}<a name="line.757"></a>
<FONT color="green">758</FONT>         * @since 3.1<a name="line.758"></a>
<FONT color="green">759</FONT>         */<a name="line.759"></a>
<FONT color="green">760</FONT>        public boolean isSupportConnected() {<a name="line.760"></a>
<FONT color="green">761</FONT>            return true;<a name="line.761"></a>
<FONT color="green">762</FONT>        }<a name="line.762"></a>
<FONT color="green">763</FONT>    <a name="line.763"></a>
<FONT color="green">764</FONT>        /**<a name="line.764"></a>
<FONT color="green">765</FONT>         * {@inheritDoc}<a name="line.765"></a>
<FONT color="green">766</FONT>         * @since 3.1<a name="line.766"></a>
<FONT color="green">767</FONT>         */<a name="line.767"></a>
<FONT color="green">768</FONT>        @Override<a name="line.768"></a>
<FONT color="green">769</FONT>        public double sample() {<a name="line.769"></a>
<FONT color="green">770</FONT>            return getNextValue();<a name="line.770"></a>
<FONT color="green">771</FONT>        }<a name="line.771"></a>
<FONT color="green">772</FONT>    <a name="line.772"></a>
<FONT color="green">773</FONT>        /**<a name="line.773"></a>
<FONT color="green">774</FONT>         * {@inheritDoc}<a name="line.774"></a>
<FONT color="green">775</FONT>         * @since 3.1<a name="line.775"></a>
<FONT color="green">776</FONT>         */<a name="line.776"></a>
<FONT color="green">777</FONT>        @Override<a name="line.777"></a>
<FONT color="green">778</FONT>        public void reseedRandomGenerator(long seed) {<a name="line.778"></a>
<FONT color="green">779</FONT>            randomData.reSeed(seed);<a name="line.779"></a>
<FONT color="green">780</FONT>        }<a name="line.780"></a>
<FONT color="green">781</FONT>    <a name="line.781"></a>
<FONT color="green">782</FONT>        /**<a name="line.782"></a>
<FONT color="green">783</FONT>         * The probability of bin i.<a name="line.783"></a>
<FONT color="green">784</FONT>         *<a name="line.784"></a>
<FONT color="green">785</FONT>         * @param i the index of the bin<a name="line.785"></a>
<FONT color="green">786</FONT>         * @return the probability that selection begins in bin i<a name="line.786"></a>
<FONT color="green">787</FONT>         */<a name="line.787"></a>
<FONT color="green">788</FONT>        private double pB(int i) {<a name="line.788"></a>
<FONT color="green">789</FONT>            return i == 0 ? upperBounds[0] :<a name="line.789"></a>
<FONT color="green">790</FONT>                upperBounds[i] - upperBounds[i - 1];<a name="line.790"></a>
<FONT color="green">791</FONT>        }<a name="line.791"></a>
<FONT color="green">792</FONT>    <a name="line.792"></a>
<FONT color="green">793</FONT>        /**<a name="line.793"></a>
<FONT color="green">794</FONT>         * The combined probability of the bins up to but not including bin i.<a name="line.794"></a>
<FONT color="green">795</FONT>         *<a name="line.795"></a>
<FONT color="green">796</FONT>         * @param i the index of the bin<a name="line.796"></a>
<FONT color="green">797</FONT>         * @return the probability that selection begins in a bin below bin i.<a name="line.797"></a>
<FONT color="green">798</FONT>         */<a name="line.798"></a>
<FONT color="green">799</FONT>        private double pBminus(int i) {<a name="line.799"></a>
<FONT color="green">800</FONT>            return i == 0 ? 0 : upperBounds[i - 1];<a name="line.800"></a>
<FONT color="green">801</FONT>        }<a name="line.801"></a>
<FONT color="green">802</FONT>    <a name="line.802"></a>
<FONT color="green">803</FONT>        /**<a name="line.803"></a>
<FONT color="green">804</FONT>         * Mass of bin i under the within-bin kernel of the bin.<a name="line.804"></a>
<FONT color="green">805</FONT>         *<a name="line.805"></a>
<FONT color="green">806</FONT>         * @param i index of the bin<a name="line.806"></a>
<FONT color="green">807</FONT>         * @return the difference in the within-bin kernel cdf between the<a name="line.807"></a>
<FONT color="green">808</FONT>         * upper and lower endpoints of bin i<a name="line.808"></a>
<FONT color="green">809</FONT>         */<a name="line.809"></a>
<FONT color="green">810</FONT>        @SuppressWarnings("deprecation")<a name="line.810"></a>
<FONT color="green">811</FONT>        private double kB(int i) {<a name="line.811"></a>
<FONT color="green">812</FONT>            final double[] binBounds = getUpperBounds();<a name="line.812"></a>
<FONT color="green">813</FONT>            final RealDistribution kernel = getKernel(binStats.get(i));<a name="line.813"></a>
<FONT color="green">814</FONT>            return i == 0 ? kernel.cumulativeProbability(min, binBounds[0]) :<a name="line.814"></a>
<FONT color="green">815</FONT>                kernel.cumulativeProbability(binBounds[i - 1], binBounds[i]);<a name="line.815"></a>
<FONT color="green">816</FONT>        }<a name="line.816"></a>
<FONT color="green">817</FONT>    <a name="line.817"></a>
<FONT color="green">818</FONT>        /**<a name="line.818"></a>
<FONT color="green">819</FONT>         * The within-bin kernel of the bin that x belongs to.<a name="line.819"></a>
<FONT color="green">820</FONT>         *<a name="line.820"></a>
<FONT color="green">821</FONT>         * @param x the value to locate within a bin<a name="line.821"></a>
<FONT color="green">822</FONT>         * @return the within-bin kernel of the bin containing x<a name="line.822"></a>
<FONT color="green">823</FONT>         */<a name="line.823"></a>
<FONT color="green">824</FONT>        private RealDistribution k(double x) {<a name="line.824"></a>
<FONT color="green">825</FONT>            final int binIndex = findBin(x);<a name="line.825"></a>
<FONT color="green">826</FONT>            return getKernel(binStats.get(binIndex));<a name="line.826"></a>
<FONT color="green">827</FONT>        }<a name="line.827"></a>
<FONT color="green">828</FONT>    <a name="line.828"></a>
<FONT color="green">829</FONT>        /**<a name="line.829"></a>
<FONT color="green">830</FONT>         * The combined probability of the bins up to and including binIndex.<a name="line.830"></a>
<FONT color="green">831</FONT>         *<a name="line.831"></a>
<FONT color="green">832</FONT>         * @param binIndex maximum bin index<a name="line.832"></a>
<FONT color="green">833</FONT>         * @return sum of the probabilities of bins through binIndex<a name="line.833"></a>
<FONT color="green">834</FONT>         */<a name="line.834"></a>
<FONT color="green">835</FONT>        private double cumBinP(int binIndex) {<a name="line.835"></a>
<FONT color="green">836</FONT>            return upperBounds[binIndex];<a name="line.836"></a>
<FONT color="green">837</FONT>        }<a name="line.837"></a>
<FONT color="green">838</FONT>    <a name="line.838"></a>
<FONT color="green">839</FONT>        /**<a name="line.839"></a>
<FONT color="green">840</FONT>         * The within-bin smoothing kernel.<a name="line.840"></a>
<FONT color="green">841</FONT>         *<a name="line.841"></a>
<FONT color="green">842</FONT>         * @param bStats summary statistics for the bin<a name="line.842"></a>
<FONT color="green">843</FONT>         * @return within-bin kernel parameterized by bStats<a name="line.843"></a>
<FONT color="green">844</FONT>         */<a name="line.844"></a>
<FONT color="green">845</FONT>        private RealDistribution getKernel(SummaryStatistics bStats) {<a name="line.845"></a>
<FONT color="green">846</FONT>            // For now, hard-code Gaussian (only kernel supported)<a name="line.846"></a>
<FONT color="green">847</FONT>            return new NormalDistribution(<a name="line.847"></a>
<FONT color="green">848</FONT>                    bStats.getMean(), bStats.getStandardDeviation());<a name="line.848"></a>
<FONT color="green">849</FONT>        }<a name="line.849"></a>
<FONT color="green">850</FONT>    }<a name="line.850"></a>




























































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